Artificial intelligence, end to end: statistics and data, classical machine learning, deep learning and reinforcement learning, quantitative finance, the complete LLM stack, prompting and agent engineering. Thirteen tracks, full mathematics, runnable Python, a live instrument for nearly every concept, and every claim cited to its source.
The Foundations track assumes only high-school algebra and builds up to the transformer. Every chapter also stands on its own, so you can start wherever you came for.
Every chapter is a guided lesson player: short lessons with a video, a live demo, and an exercise. Use Read in any chapter to see the whole thing as one page.
Pick a goal and a depth to get a recommended starting chapter. The full map is below.